Object locating and tracking algorithms are known, and the features of these algorithms are varied. For example, U.S. Pat. No. 9,171,229 (Hsieh et al.) describes a visual object tracking method entailing setting an object window having a target in a video image, defining a search window greater than the object window, analyzing an image pixel of the object window to generate a color histogram for defining a color filter which includes a dominant color characteristic of the target, and using the color filter to generate an object template and a dominant color map in the object window and the search window respectively. The object template includes a shape characteristic of the target, while the dominant color map includes at least one candidate block. Similarity between the object template and the candidate block is compared to obtain a probability distribution map, and the probability distribution map is used to compute the mass center of the target. The method generates the probability map by the color and shape characteristics to compute the mass center.
U.S. Pat. No. 9,129,397 (Choi et al.) describes a human tracking method using a color histogram is that can allegedly more adaptively perform human tracking using different target color histograms according to the human poses, instead of applying only one target color histogram to the tracking process of one person, such that the accuracy of human tracking can be increased. The human tracking method entails performing color space conversion of input video data, calculating a state equation of a particle based on the color-space conversion data, calculating the state equation, and calculating human pose-adaptive observation likelihood, resampling the particle using the observation likelihood, and then estimating a state value of the human and updating a target color histogram.
U.S. Pat. No. 8,478,040 (Brogren et al.) describes an identification apparatus in a video surveillance system for identifying properties of an object captured in a video sequence by a video surveillance camera. The identification apparatus includes an object identification unit for identifying a specific object in a video sequence, a color histogram generator for generating a color histogram in at least two dimensions of a color space based on color and intensity information of the specific object identified in the video sequence, the color and intensity information originating from a plurality of images of the video sequence, and an object properties identificator for identifying properties of the object based on the generated color histogram. The identified properties can then allegedly be used in a tracking device of the video surveillance system for tracking an object between different video sequences, which may be captured by two different video surveillance cameras. A corresponding method for identifying properties of an object captured in a video sequence and a method for tracking the object in a video surveillance system are also described.